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All Journal EMITTER International Journal of Engineering Technology Letters in Information Technology Education (LITE)
Bataona, Daniel Silli
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Computer Science & IT Education

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MAIL ARCHIVE SYSTEM MODEL USING ADVANTAGE DATABASE SERVER (ADS) Manulangga, Gloria Christina; Bataona, Daniel Silli; Laumal, Folkes Eduard
Letters in Information Technology Education (LITE) Vol 1, No 1 (2018)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (590.658 KB) | DOI: 10.17977/um010v1i12018p009

Abstract

Computerization process in archiving activity is completely needed and already many kinds of archiving model application. One of those models is Advantage Database Server (ADS) that support table system and data access based on SQL. This model is also flexible and easy to apply on institution infrastructure. This research aims to prove that the model can improve the productivity of an institution on archiving activity. The development method used is a prototype with user acceptance system testing. The result shows that there are average time reduction of about 50.8% on data saving, 95.1% on data searching, and 93.9% on report printing.
Comparison of Adaptive Ant Colony Optimization for Image Edge Detection of Leaves Bone Structure Liantoni, Febri; Perwira, Rifki Indra; Bataona, Daniel Silli
EMITTER International Journal of Engineering Technology Vol 6 No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (455.566 KB) | DOI: 10.24003/emitter.v6i2.306

Abstract

Leaf bone structure has a characteristic that can be used as a reference in digital image processing. One form of digital image processing is image edge detection. Edge detection is the process of extracting edge information from an image. In this research, Adaptive Ant Colony Optimization algorithm is proposed for edge image detection of leaf bone structure. The Adaptive Ant Colony Optimization method is a modification of Ant Colony Optimization, in which the initial an ant dissemination process is no longer random, but it is done by a pixel placement process that allows for an edge based on the value of the image gradient. As a comparison also performed edge detection using Robert and Sobel method. Based on the experiments performed, Adaptive Ant Colony Optimization algorithm is capable of producing more detailed image edge detection and has thicker borders than others. Keywords: edge detection, ant colony optimization, robert, sobel
Co-Authors Febri Liantoni, Febri Laumal, Folkes Eduard Manulangga, Gloria Christina Rifki Indra Perwira